EP3666424B1 - Procédé de surveillance de bassin de fusion utilisant des dimensions fractales - Google Patents

Procédé de surveillance de bassin de fusion utilisant des dimensions fractales Download PDF

Info

Publication number
EP3666424B1
EP3666424B1 EP19210320.8A EP19210320A EP3666424B1 EP 3666424 B1 EP3666424 B1 EP 3666424B1 EP 19210320 A EP19210320 A EP 19210320A EP 3666424 B1 EP3666424 B1 EP 3666424B1
Authority
EP
European Patent Office
Prior art keywords
melt pool
fractal dimension
additive manufacturing
manufacturing process
boundary
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Active
Application number
EP19210320.8A
Other languages
German (de)
English (en)
Other versions
EP3666424A1 (fr
Inventor
Thomas Graham Spears
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
General Electric Co
Original Assignee
General Electric Co
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by General Electric Co filed Critical General Electric Co
Publication of EP3666424A1 publication Critical patent/EP3666424A1/fr
Application granted granted Critical
Publication of EP3666424B1 publication Critical patent/EP3666424B1/fr
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Images

Classifications

    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B33—ADDITIVE MANUFACTURING TECHNOLOGY
    • B33Y—ADDITIVE MANUFACTURING, i.e. MANUFACTURING OF THREE-DIMENSIONAL [3-D] OBJECTS BY ADDITIVE DEPOSITION, ADDITIVE AGGLOMERATION OR ADDITIVE LAYERING, e.g. BY 3-D PRINTING, STEREOLITHOGRAPHY OR SELECTIVE LASER SINTERING
    • B33Y10/00—Processes of additive manufacturing
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B22—CASTING; POWDER METALLURGY
    • B22F—WORKING METALLIC POWDER; MANUFACTURE OF ARTICLES FROM METALLIC POWDER; MAKING METALLIC POWDER; APPARATUS OR DEVICES SPECIALLY ADAPTED FOR METALLIC POWDER
    • B22F10/00—Additive manufacturing of workpieces or articles from metallic powder
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/70—Determining position or orientation of objects or cameras
    • G06T7/73—Determining position or orientation of objects or cameras using feature-based methods
    • G06T7/74—Determining position or orientation of objects or cameras using feature-based methods involving reference images or patches
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B22—CASTING; POWDER METALLURGY
    • B22F—WORKING METALLIC POWDER; MANUFACTURE OF ARTICLES FROM METALLIC POWDER; MAKING METALLIC POWDER; APPARATUS OR DEVICES SPECIALLY ADAPTED FOR METALLIC POWDER
    • B22F10/00—Additive manufacturing of workpieces or articles from metallic powder
    • B22F10/80—Data acquisition or data processing
    • B22F10/85—Data acquisition or data processing for controlling or regulating additive manufacturing processes
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B22—CASTING; POWDER METALLURGY
    • B22F—WORKING METALLIC POWDER; MANUFACTURE OF ARTICLES FROM METALLIC POWDER; MAKING METALLIC POWDER; APPARATUS OR DEVICES SPECIALLY ADAPTED FOR METALLIC POWDER
    • B22F12/00—Apparatus or devices specially adapted for additive manufacturing; Auxiliary means for additive manufacturing; Combinations of additive manufacturing apparatus or devices with other processing apparatus or devices
    • B22F12/90—Means for process control, e.g. cameras or sensors
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B29—WORKING OF PLASTICS; WORKING OF SUBSTANCES IN A PLASTIC STATE IN GENERAL
    • B29C—SHAPING OR JOINING OF PLASTICS; SHAPING OF MATERIAL IN A PLASTIC STATE, NOT OTHERWISE PROVIDED FOR; AFTER-TREATMENT OF THE SHAPED PRODUCTS, e.g. REPAIRING
    • B29C64/00—Additive manufacturing, i.e. manufacturing of three-dimensional [3D] objects by additive deposition, additive agglomeration or additive layering, e.g. by 3D printing, stereolithography or selective laser sintering
    • B29C64/10—Processes of additive manufacturing
    • B29C64/141—Processes of additive manufacturing using only solid materials
    • B29C64/153—Processes of additive manufacturing using only solid materials using layers of powder being selectively joined, e.g. by selective laser sintering or melting
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B29—WORKING OF PLASTICS; WORKING OF SUBSTANCES IN A PLASTIC STATE IN GENERAL
    • B29C—SHAPING OR JOINING OF PLASTICS; SHAPING OF MATERIAL IN A PLASTIC STATE, NOT OTHERWISE PROVIDED FOR; AFTER-TREATMENT OF THE SHAPED PRODUCTS, e.g. REPAIRING
    • B29C64/00—Additive manufacturing, i.e. manufacturing of three-dimensional [3D] objects by additive deposition, additive agglomeration or additive layering, e.g. by 3D printing, stereolithography or selective laser sintering
    • B29C64/30—Auxiliary operations or equipment
    • B29C64/386—Data acquisition or data processing for additive manufacturing
    • B29C64/393—Data acquisition or data processing for additive manufacturing for controlling or regulating additive manufacturing processes
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B33—ADDITIVE MANUFACTURING TECHNOLOGY
    • B33Y—ADDITIVE MANUFACTURING, i.e. MANUFACTURING OF THREE-DIMENSIONAL [3-D] OBJECTS BY ADDITIVE DEPOSITION, ADDITIVE AGGLOMERATION OR ADDITIVE LAYERING, e.g. BY 3-D PRINTING, STEREOLITHOGRAPHY OR SELECTIVE LASER SINTERING
    • B33Y40/00—Auxiliary operations or equipment, e.g. for material handling
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B33—ADDITIVE MANUFACTURING TECHNOLOGY
    • B33Y—ADDITIVE MANUFACTURING, i.e. MANUFACTURING OF THREE-DIMENSIONAL [3-D] OBJECTS BY ADDITIVE DEPOSITION, ADDITIVE AGGLOMERATION OR ADDITIVE LAYERING, e.g. BY 3-D PRINTING, STEREOLITHOGRAPHY OR SELECTIVE LASER SINTERING
    • B33Y50/00—Data acquisition or data processing for additive manufacturing
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/0002—Inspection of images, e.g. flaw detection
    • G06T7/0004—Industrial image inspection
    • G06T7/001—Industrial image inspection using an image reference approach
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/40—Analysis of texture
    • G06T7/41—Analysis of texture based on statistical description of texture
    • G06T7/48—Analysis of texture based on statistical description of texture using fractals
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B22—CASTING; POWDER METALLURGY
    • B22F—WORKING METALLIC POWDER; MANUFACTURE OF ARTICLES FROM METALLIC POWDER; MAKING METALLIC POWDER; APPARATUS OR DEVICES SPECIALLY ADAPTED FOR METALLIC POWDER
    • B22F10/00—Additive manufacturing of workpieces or articles from metallic powder
    • B22F10/20—Direct sintering or melting
    • B22F10/25—Direct deposition of metal particles, e.g. direct metal deposition [DMD] or laser engineered net shaping [LENS]
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B22—CASTING; POWDER METALLURGY
    • B22F—WORKING METALLIC POWDER; MANUFACTURE OF ARTICLES FROM METALLIC POWDER; MAKING METALLIC POWDER; APPARATUS OR DEVICES SPECIALLY ADAPTED FOR METALLIC POWDER
    • B22F10/00—Additive manufacturing of workpieces or articles from metallic powder
    • B22F10/20—Direct sintering or melting
    • B22F10/28—Powder bed fusion, e.g. selective laser melting [SLM] or electron beam melting [EBM]
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B22—CASTING; POWDER METALLURGY
    • B22F—WORKING METALLIC POWDER; MANUFACTURE OF ARTICLES FROM METALLIC POWDER; MAKING METALLIC POWDER; APPARATUS OR DEVICES SPECIALLY ADAPTED FOR METALLIC POWDER
    • B22F10/00—Additive manufacturing of workpieces or articles from metallic powder
    • B22F10/30—Process control
    • B22F10/36—Process control of energy beam parameters
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B22—CASTING; POWDER METALLURGY
    • B22F—WORKING METALLIC POWDER; MANUFACTURE OF ARTICLES FROM METALLIC POWDER; MAKING METALLIC POWDER; APPARATUS OR DEVICES SPECIALLY ADAPTED FOR METALLIC POWDER
    • B22F10/00—Additive manufacturing of workpieces or articles from metallic powder
    • B22F10/70—Recycling
    • B22F10/73—Recycling of powder
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B22—CASTING; POWDER METALLURGY
    • B22F—WORKING METALLIC POWDER; MANUFACTURE OF ARTICLES FROM METALLIC POWDER; MAKING METALLIC POWDER; APPARATUS OR DEVICES SPECIALLY ADAPTED FOR METALLIC POWDER
    • B22F12/00—Apparatus or devices specially adapted for additive manufacturing; Auxiliary means for additive manufacturing; Combinations of additive manufacturing apparatus or devices with other processing apparatus or devices
    • B22F12/40—Radiation means
    • B22F12/44—Radiation means characterised by the configuration of the radiation means
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B22—CASTING; POWDER METALLURGY
    • B22F—WORKING METALLIC POWDER; MANUFACTURE OF ARTICLES FROM METALLIC POWDER; MAKING METALLIC POWDER; APPARATUS OR DEVICES SPECIALLY ADAPTED FOR METALLIC POWDER
    • B22F12/00—Apparatus or devices specially adapted for additive manufacturing; Auxiliary means for additive manufacturing; Combinations of additive manufacturing apparatus or devices with other processing apparatus or devices
    • B22F12/60—Planarisation devices; Compression devices
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B22—CASTING; POWDER METALLURGY
    • B22F—WORKING METALLIC POWDER; MANUFACTURE OF ARTICLES FROM METALLIC POWDER; MAKING METALLIC POWDER; APPARATUS OR DEVICES SPECIALLY ADAPTED FOR METALLIC POWDER
    • B22F12/00—Apparatus or devices specially adapted for additive manufacturing; Auxiliary means for additive manufacturing; Combinations of additive manufacturing apparatus or devices with other processing apparatus or devices
    • B22F12/70—Gas flow means
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B33—ADDITIVE MANUFACTURING TECHNOLOGY
    • B33Y—ADDITIVE MANUFACTURING, i.e. MANUFACTURING OF THREE-DIMENSIONAL [3-D] OBJECTS BY ADDITIVE DEPOSITION, ADDITIVE AGGLOMERATION OR ADDITIVE LAYERING, e.g. BY 3-D PRINTING, STEREOLITHOGRAPHY OR SELECTIVE LASER SINTERING
    • B33Y50/00—Data acquisition or data processing for additive manufacturing
    • B33Y50/02—Data acquisition or data processing for additive manufacturing for controlling or regulating additive manufacturing processes
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/30—Subject of image; Context of image processing
    • G06T2207/30108—Industrial image inspection
    • G06T2207/30144—Printing quality
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
    • Y02P10/00—Technologies related to metal processing
    • Y02P10/25—Process efficiency

Definitions

  • This invention relates generally to additive manufacturing and related processes, and more particularly to apparatus and methods for melt pool monitoring and process control in additive manufacturing.
  • Additive manufacturing is a process in which material is built up layer-by-layer to form a component. Additive manufacturing is limited primarily by the position resolution of the machine and not limited by requirements for providing draft angles, avoiding overhangs, etc. as required by casting. Additive manufacturing is also referred to by terms such as “layered manufacturing,” “reverse machining,” “direct metal laser melting” (DMLM), and “3-D printing”. Such terms are treated as synonyms for purposes of the present invention.
  • a "powder bed” machine One type of additive manufacturing machine is referred to as a "powder bed” machine and includes a build chamber that encloses a mass of powder which is selectively fused by a laser to form a workpiece.
  • US 2008/314878 A1 discloses an imaging-based monitoring principle for an AM-process.
  • BING YAO ET AL: "Multifractal Analysis of Image Profiles for the Characterization and Detection of Defects in Additive Manufacturing",JOURNAL OF MANUFACTURING SCIENCE AND ENGINEERING, vol. 140, no. 3, 3 January 2018 (2018-01-03 ) discloses a multifractal methodology for the characterization and detection of defects in PBF-AM parts.
  • One problem with prior art additive manufacturing machines is that they operate in an open loop environment and cannot report back to an operator the stability of the process being applied. The systems in place to determine health of the process occur in quality steps after the build has finished. When issues are caught there can be work in progress that is scrapped due to machine issues that were undetected till the ex post facto quality system could catch them.
  • FIG. 1 illustrates schematically an additive manufacturing machine 10 suitable for carrying out an additive manufacturing method.
  • the machine 10 and its operation are as representative example of a "powder bed machine”.
  • the machine 10 is merely used as an example to provide context for describing the principles of the present invention.
  • the principles described herein are applicable to other configurations of powder bed machines, as well as to other types of additive manufacturing machines and related processes. More generally, the principles described herein would be applicable to any manufacturing process in which a melt pool is generated. Nonlimiting examples of such processes include electron-beam melting (“EBM”), directed energy deposition (“DED”), and laser welding.
  • EBM electron-beam melting
  • DED directed energy deposition
  • laser welding laser welding.
  • the term “manufacturing process” could also encompass repair processes where components are built up or joined together using a technique that generates a melt pool.
  • Basic components of the machine 10 include a table 12, a powder supply 14, a recoater 16, an overflow container 18, a build platform 20 surrounded by a build chamber 22, a directed energy source 24, and a beam steering apparatus 26, all surrounded by a housing 28. Each of these components will be described in more detail below.
  • the table 12 is a rigid structure defining a planar worksurface 30.
  • the worksurface 30 is coplanar with and defines a virtual workplane. In the illustrated example it includes a build opening 32 communicating with the build chamber 22 and exposing the build platform 20, a supply opening 34 communicating with the powder supply 14, and an overflow opening 36 communicating with the overflow container 18.
  • the recoater 16 is a rigid, laterally-elongated structure that lies on the worksurface 30. It is connected to an actuator 38 operable to selectively move the recoater 16 along the worksurface 30.
  • the actuator 38 is depicted schematically in FIG. 1 , with the understanding devices such as pneumatic or hydraulic cylinders, ballscrew or linear electric actuators, and so forth, may be used for this purpose.
  • the powder supply 14 comprises a supply container 40 underlying and communicating with the supply opening 34, and an elevator 42.
  • the elevator 42 is a plate-like structure that is vertically slidable within the supply container 40. It is connected to an actuator 44 operable to selectively move the elevator 42 up or down.
  • the actuator 44 is depicted schematically in FIG. 1 , with the understanding that devices such as pneumatic or hydraulic cylinders, ballscrew or linear electric actuators, and so forth, may be used for this purpose.
  • a supply of powder "P" of a desired composition for example, metallic, ceramic, and/or organic powder
  • Other types of powder supplies may be used; for example, powder may be dropped into the build chamber 22 by an overhead device (not shown).
  • the build platform 20 is a plate-like structure that is vertically slidable below the build opening 32. It is connected to an actuator 46 operable to selectively move the build platform 20 up or down.
  • the actuator 46 is depicted schematically in FIG. 1 , with the understanding that devices such as pneumatic or hydraulic cylinders, ballscrew or linear electric actuators, and so forth, may be used for this purpose.
  • the overflow container 18 underlies and communicates with the overflow opening 36, and serves as a repository for excess powder P.
  • the directed energy source 24 may comprise any device operable to generate a beam of suitable power and other operating characteristics to melt and fuse the powder P during the build process, described in more detail below.
  • the directed energy source 24 may be a laser.
  • Other directed-energy sources such as electron beam guns are suitable alternatives to a laser.
  • the beam steering apparatus 26 may include one or more mirrors, prisms, and/or lenses and provided with suitable actuators, and arranged so that a beam "B" from the directed energy source 24 can be focused to a desired spot size and steered to a desired position in plane coincident with the worksurface 30.
  • this plane may be referred to as a X-Y plane, and a direction perpendicular to the X-Y plane is denoted as a Z-direction (X, Y, and Z being three mutually perpendicular directions).
  • the beam B may be referred to herein as a "build beam".
  • the housing 28 serves to isolate and protect the other components of the machine 10. During the build process described above, the housing 28 is provided with a flow of an appropriate shielding gas which, among other functions, excludes oxygen from the build environment. To provide this flow the machine 10 may be coupled to a gas flow apparatus 54, seen in FIG. 2 .
  • the exemplary gas flow apparatus 54 includes, in serial fluid flow communication, a variable-speed fan 56, a filter 58, an inlet duct 60 communicating with the housing 28, and a return duct 64 communicating with the housing 28. All of the components of the gas flow apparatus 54 are interconnected with suitable ducting and define a gas flow circuit in combination with the housing 28.
  • the composition of the gas used may similar to that used as shielding gas for conventional welding operations.
  • gases such as nitrogen, argon, or mixtures thereof may be used.
  • Any convenient source of gas may be used.
  • the gas is nitrogen, a conventional nitrogen generator 66 may be connected to the gas flow apparatus 54.
  • the gas could be supplied using one or more pressurized cylinders 68.
  • An exemplary basic build process for a workpiece W using the apparatus described above is as follows.
  • the build platform 20 is moved to an initial high position.
  • the build platform 20 is lowered below the worksurface 30 by a selected layer increment.
  • the layer increment affects the speed of the additive manufacturing process and the resolution of the workpiece W.
  • the layer increment may be about 10 to 50 micrometers (0.0003 to 0.002 in.).
  • Powder "P" is then deposited over the build platform 20 for example, the elevator 42 of the supply container 40 may be raised to push powder through the supply opening 34, exposing it above the worksurface 30.
  • the recoater 16 is moved across the worksurface to spread the raised powder P horizontally over the build platform 20.
  • the leveled powder P may be referred to as a "build layer” and the exposed upper surface thereof may be referred to as a "build surface”.
  • the directed energy source 24 is used to melt a two-dimensional cross-section or layer of the workpiece W being built.
  • the directed energy source 24 emits a beam "B" and the beam steering apparatus 26 is used to steer a focal spot of the build beam B over the exposed powder surface in an appropriate pattern.
  • a small portion of exposed layer of the powder P surrounding the focal spot, referred to herein as a "melt pool" 52 is heated by the build beam B to a temperature allowing it to sinter or melt, flow, and consolidate.
  • the melt pool 52 may be on the order of 100 micrometers (0.004 in.) wide. This step may be referred to as fusing the powder P.
  • the build platform 20 is moved vertically downward by the layer increment, and another layer of powder P is applied in a similar thickness.
  • the directed energy source 24 again emits a build beam B and the beam steering apparatus 26 is used to steer the focal spot of the build beam B over the exposed powder surface in an appropriate pattern.
  • the exposed layer of the powder P is heated by the build beam B to a temperature allowing it to sinter or melt, flow, and consolidate both within the top layer and with the lower, previously-solidified layer.
  • This cycle of moving the build platform 20, applying powder P, and then directed energy fusing the powder P is repeated until the entire workpiece W is complete.
  • the additive manufacturing machine 10 is provided with an imaging apparatus 70 which is operable to produce a digital image of the melt pool 52 comprising an array of individual image elements, i.e., pixels for a 2-D array or voxels for a 3-D array.
  • An example of such an image 72 is shown in FIG. 3 , with image elements 74.
  • the imaging apparatus 70 is operable to produce, for each image element, a measurement of at least one physical property.
  • the measurement may include at least one scalar value such as brightness, intensity, frequency, temperature, or Z-height.
  • the imaging apparatus 70 may produce a signal representative of multiple factors, for example RGB color values.
  • the imaging apparatus 70 is also operable to produce relative or absolute positional information for each imaging element.
  • the output of the imaging apparatus 70 for a particular image element 74 may be in the format X, Y, T where X equals X-position, Y equals Y-position, and T equals temperature.
  • Nonlimiting examples of suitable imaging apparatus 70 include photodiode arrays, photomultiplier tube (“PMT”) arrays, digital cameras (e.g. CMOS or CCD), or optical coherence tomography (“OCT”) apparatus.
  • PMT photomultiplier tube
  • OCT optical coherence tomography
  • X and Y information e.g., "3-D information”
  • the imaging apparatus 70 is depicted as a digital camera placed so that its field-of-view encompasses the melt pool 52.
  • the imaging apparatus 70 may be statically mounted or it may be mounted so that it can be driven by one or more actuators (not shown) in order to track the position of the melt pool 52.
  • the imaging apparatus 70 may be configured to acquire a series of static images at regular intervals, or it may operate continuously.
  • the melt pool images 72 create a base dataset on which analysis may be performed.
  • the next step is to determine a boundary of the melt pool 52 based on the image 72 produced by the imaging apparatus 70.
  • the process of determining a boundary of the melt pool 52 may be carried out using appropriately-programmed software running on one or more processors embodied in a device such as a microcomputer (not shown).
  • a device such as a microcomputer (not shown).
  • Such software may be implemented on a device separate from the machine 10, or it may be incorporated into the machine 10, for example the software may be run by the controller described below.
  • melt pool 52 a portion of the powder bed P is shown with a melt pool 52 superimposed thereon.
  • the melt pool 52 is shown having a peripheral melt pool boundary 76 or closed perimeter, identified by the shaded image elements 74, which is a demarcation between the interior of the melt pool 52 and the exterior of the melt pool 52.
  • a threshold value may be established, and the melt pool boundary 76 may include any image elements which are equal to the threshold value.
  • FIG. 4 shows a simplified representation of a portion of the melt pool 52 in which each image element 74 is assigned a scalar value corresponding to sensed data. For example, temperature data might be represented on a 0-10 scale.
  • the threshold value is "4" (this is an arbitrary value used as an example). Accordingly, each image element 74 returning the value 4 is declared or defined to constitute a portion of the melt pool boundary 76. Any image element 74 returning a value greater than 4 is declared or defined to be inside the melt pool 52, and any image element 74 returning a value less than 4 is declared or defined to be outside the melt pool 52.
  • the threshold value may include a range or band of values, for the purpose of resolving ambiguity.
  • the threshold value representing inclusion in the melt pool boundary 76 might be any value greater than 3.0 and less than 5.0.
  • the range of sensor values and the threshold value or threshold range may be stored in a calibration table which is then referenced by the software to evaluate the melt pool 52 during machine operation.
  • the values for the calibration table may be determined analytically or empirically.
  • the criteria for determining the location of the melt pool boundary 76 may be based on a simple scalar value in a 2-D image as described in the above example, for example temperature, image element intensity, etc.
  • Another 2-D property or combination of properties such as image element color, emission frequency, or image element sheen may be used as a criteria for determining the location of the melt pool boundary 76.
  • Such properties are combination of properties may be more directly indicative of the presence of a difference in phase (liquid versus solid), or of melting or incipient melting.
  • a 3-D property or combination of properties may be used as a criteria for determining location of the melt pool boundary 76.
  • a height increase or decrease relative to the surrounding material may be indicative of the presence of the difference in phase (liquid versus solid), or of melting or incipient melting.
  • the output of the boundary determination process described above is a digital map of the melt pool boundary 76.
  • the process of determining the location of the melt pool boundary 76 may be referred to as "mapping the melt pool boundary".
  • melt pool boundary 76 Once the melt pool boundary 76 is established, one or more geometric analytical constructs may be used to analyze the boundary and determine the quality of the melt pool 52.
  • melt pool boundary 76 One analytical construct for evaluating the melt pool boundary 76 is to consider its fractal dimension.
  • the fractal dimension "D" of a shape is a parameter that quantifies its relative complexity as a ratio of change in detail to change in scale.
  • the fractal dimension does not uniquely define a shape.
  • D log n log 1 / s
  • n is the number of line segments used to bound the shape and s is a scaling factor.
  • s is a scaling factor.
  • FIG. 5 illustrates a simplified 3-D representation 172 of a portion of the melt pool 52 in which each image element 174 is assigned an elevation (Z-axis height) corresponding to sensed data, for example a scalar quantity such as pixel intensity.
  • a fractal dimension may be computed for the surface 172 using known techniques.
  • the fractal dimension once computed, provides a parameter that can be used to evaluate the melt pool boundary 76.
  • the fractal dimension D of the melt pool boundary 76 shown bounded by line segments 77, would be approximately 1.065.
  • a ratio of the melt pool intensity to the fractal dimension may be used as a figure of merit.
  • a limit value may be established for the fractal dimension or ratio described above as a basis for concluding that the melt pool 52 is acceptable or not, corresponding to the additive manufacturing process being "unfaulted” or "faulted”.
  • FIG. 6 depicts a model of an idealized melt pool template 78.
  • the melt pool template 78 is made up of image elements 80 and includes a predetermined template boundary 82 which is representative of a known good process (i.e., unfaulted).
  • the template boundary 82 is approximately circular and would have a fractal dimension of 1. While no specific shape is necessarily required for an acceptable process, it is generally true that the more complex shape of FIG. 3 , having a higher fractal dimension, is more likely to be unacceptable and indicative of a process problem, than a less complex shape. Accordingly, in this example, a limit value could be set somewhere in the range between 1 and 1.065.
  • software may be used to compute the fractal dimension based on the measured data. If the fractal dimension exceeds the limit value, the melt pool boundary 76 of the melt pool 52 may be declared to be unacceptable (i.e., process faulted).
  • the melt pool quality determination may be repeated for each individual melt pool image 72 as they are acquired.
  • the computed fractal dimension for each melt pool image 72 may be used as an input into a single or multivariate statistical process control (“SPC") process.
  • SPC statistical process control
  • Nonlimiting examples of known SPC methods include principal component analysis (“PCA”), independent component analysis (“ICA”), and kernel PCA.
  • PCA principal component analysis
  • ICA independent component analysis
  • kernel PCA kernel PCA
  • the computed fractal dimension would be in input into one of the above-noted SPC methods along with other process parameters or extracted values from the process (such as melt pool intensity, melt pool area, etc.). The PCA could then be performed and process control could be implemented based on the reduced variables.
  • Another example would be to use the computed fractal dimension in multivariate SPC methodologies such as partial least squares ("PLS").
  • fractal dimension In PLS, one could use fractal dimension as an input for doing process control on another variable.
  • An example would be that fractal dimension, along with other possible independent variables (inputs or "Xs") would be used in PLS for predicting other dependent variable (outputs or "Ys"), such as melt pool intensity.
  • fractal dimension could be used as a dependent variable in PLS and then the methodology could be used to predict the fractal dimension, which would serve as a basis for process control.
  • the process may include creating populations of unfaulted and faulted process states based on the fractal dimension. Specifically, each melt pool image 72 would be assigned to either the unfaulted or faulted population as its fractal dimension is computed.
  • the fractal dimension of current process could be assigned to the populations of unfaulted and faulted process through a Multiple Model Hypothesis Test framework.
  • a melt pool monitoring process may be incorporated into the build process described above.
  • the monitoring process includes using the imaging apparatus 70 described above to acquire melt pool images 72, evaluating the melt pool 52 using one or more of the fractal dimension techniques described above, and then adjusting one or more process parameters as necessary.
  • process parameters can refer to any controllable aspect of the machine 10.
  • the monitoring process may include taking a discrete action in response to the fractal dimension evaluation indicating a process fault, such as providing a visual or audible alarm to a local or remote operator.
  • the monitoring process may include stopping the build process in response to fractal dimension evaluation indicating a process fault. This is another example of a discrete action.
  • the monitoring process may include real-time control of one or more process parameters, such as directed energy source power level or beam scan velocity, using a method such as: statistical process control, feedforward control, feedback control using proportional, proportional-integral, or proportional-integral-derivative control logic, neural network control algorithms, or fuzzy logic control algorithms.
  • process parameters such as directed energy source power level or beam scan velocity
  • a method such as: statistical process control, feedforward control, feedback control using proportional, proportional-integral, or proportional-integral-derivative control logic, neural network control algorithms, or fuzzy logic control algorithms.
  • the monitoring method may include monitoring of the condition or "health" of the machine 10.
  • Melt pool measurements may be measured and stored during several build cycles and compared between cycles. For example, a change in melt pool consistency between cycles could indicate machine miscalibration or degradation. Corrective action could take the form of machine maintenance or repairs, or modification of process parameters in subsequent builds to compensate for machine degradation.
  • FIG. 1 illustrates schematically a controller 84 which includes one or more processors operable to control the machine 10
  • melt pool stability using the method described herein can also reduce machine setup costs through validation of the process to a known good standard, reduce existing material development for additive, reduce application development and be an enabler for novel alloy for additive development.

Landscapes

  • Engineering & Computer Science (AREA)
  • Chemical & Material Sciences (AREA)
  • Materials Engineering (AREA)
  • Manufacturing & Machinery (AREA)
  • Physics & Mathematics (AREA)
  • Optics & Photonics (AREA)
  • Automation & Control Theory (AREA)
  • Mechanical Engineering (AREA)
  • Theoretical Computer Science (AREA)
  • General Physics & Mathematics (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Analytical Chemistry (AREA)
  • Quality & Reliability (AREA)
  • Probability & Statistics with Applications (AREA)
  • Powder Metallurgy (AREA)

Claims (15)

  1. Procédé de commande d'un processus de fabrication additive dans lequel une source d'énergie dirigée (24) est utilisée pour la fusion sélective d'un matériau pour former une pièce, formant un bassin de fusion (52) dans le processus de fusion, le procédé comprenant :
    l'utilisation d'un appareil d'imagerie pour générer une image (72) du bassin de fusion (52) comprenant un réseau d'éléments d'image individuels (74), l'image (72) incluant une mesure d'au moins une propriété physique pour chacun des éléments d'image individuels (74) ;
    à partir des mesures, le mappage d'une limite de bassin de fusion (76) du bassin de fusion (52) ;
    le calcul d'une dimension fractale du bassin de fusion (52) ; et
    la commande d'au moins un aspect du processus de fabrication additive par rapport à la dimension fractale.
  2. Procédé selon la revendication 1, dans lequel la mesure pour chacun des éléments d'image (74) inclut au moins une valeur scalaire.
  3. Procédé selon la revendication 1, dans lequel la valeur fractale est calculée pour une surface en 3D du bassin de fusion (52).
  4. Procédé selon la revendication 1 dans lequel l'étape de mappage de la limite du bassin de fusion (52) inclut :
    l'établissement d'une valeur seuil ;
    la comparaison de la mesure pour chacun des éléments d'image (74) à la valeur seuil ; et
    la définition de chacun des éléments d'image (74) qui correspond à la valeur seuil pour constituer une partie de la limite de bassin de fusion (76).
  5. Procédé selon la revendication 5, dans lequel la valeur seuil est une plage ayant des limites supérieure et inférieure prédéterminées.
  6. Procédé selon la revendication 1, comprenant en outre l'évaluation de la dimension fractale pour des indications d'une défaillance de processus.
  7. Procédé selon la revendication 6, dans lequel le dépassement par la dimension fractale d'une valeur limite prédéterminée indique une défaillance de processus.
  8. Procédé selon la revendication 1, dans lequel la dimension fractale est utilisée en tant qu'entrée dans un procédé de commande de processus statistique pour le processus de fabrication additive.
  9. Procédé selon la revendication 1, dans lequel la dimension fractale est utilisée pour créer des populations d'états de processus non défaillant et défaillant.
  10. Procédé selon la revendication 9, dans lequel la dimension fractale d'un processus actuel est attribuée aux populations de processus non défaillant et défaillant par le biais d'une structure de test d'hypothèse à modèles multiples.
  11. Procédé selon la revendication 6 dans lequel l'étape de commande inclut l'entreprise d'une action discrète en réponse à l'indication par la dimension fractale d'une défaillance de processus.
  12. Procédé selon la revendication 11 dans lequel l'action discrète stoppe le processus de fabrication additive.
  13. Procédé selon la revendication 11 dans lequel l'étape de commande inclut la modification d'au moins un paramètre de processus du processus de fabrication additive.
  14. Procédé selon la revendication 1, comprenant en outre :
    le calcul d'un rapport entre la dimension fractale et une intensité de bassin de fusion mesurée ; et
    la commande du processus de fabrication additive par rapport au rapport calculé.
  15. Procédé selon la revendication 1, dans lequel le processus de fabrication additive inclut :
    le dépôt d'un matériau dans une chambre de construction (22) ; et
    la direction du faisceau de construction à partir d'une source d'énergie dirigée (24) pour faire fondre sélectivement le matériau dans un schéma correspondant à la couche en coupe transversale de la pièce, dans lequel le bassin de fusion (52) est formé par la source d'énergie dirigée (24).
EP19210320.8A 2018-12-13 2019-11-20 Procédé de surveillance de bassin de fusion utilisant des dimensions fractales Active EP3666424B1 (fr)

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
US16/219,474 US11020907B2 (en) 2018-12-13 2018-12-13 Method for melt pool monitoring using fractal dimensions

Publications (2)

Publication Number Publication Date
EP3666424A1 EP3666424A1 (fr) 2020-06-17
EP3666424B1 true EP3666424B1 (fr) 2023-02-08

Family

ID=68621152

Family Applications (1)

Application Number Title Priority Date Filing Date
EP19210320.8A Active EP3666424B1 (fr) 2018-12-13 2019-11-20 Procédé de surveillance de bassin de fusion utilisant des dimensions fractales

Country Status (3)

Country Link
US (1) US11020907B2 (fr)
EP (1) EP3666424B1 (fr)
CN (1) CN111318697B (fr)

Family Cites Families (72)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US6046426A (en) 1996-07-08 2000-04-04 Sandia Corporation Method and system for producing complex-shape objects
JP3837921B2 (ja) * 1998-06-19 2006-10-25 富士ゼロックス株式会社 画像処理装置、ｃｔスキャナ及びフラクタル次元測定方法
US6925346B1 (en) 1998-06-30 2005-08-02 Jyoti Mazumder Closed-loop, rapid manufacturing of three-dimensional components using direct metal deposition
US6459951B1 (en) 1999-09-10 2002-10-01 Sandia Corporation Direct laser additive fabrication system with image feedback control
US20020142107A1 (en) 2000-07-27 2002-10-03 Jyoti Mazumder Fabrication of customized, composite, and alloy-variant components using closed-loop direct metal deposition
CN101694582B (zh) * 2001-11-17 2012-04-18 株式会社Insstek 实时监测和控制淀积高度的方法和系统
AU2003278047A1 (en) 2002-10-31 2004-05-25 Stephen F. Corbin System and method for closed-loop control of laser cladding by powder injection
US6970804B2 (en) * 2002-12-17 2005-11-29 Xerox Corporation Automated self-learning diagnostic system
US6993187B2 (en) * 2003-02-14 2006-01-31 Ikonisys, Inc. Method and system for object recognition using fractal maps
US6995334B1 (en) 2003-08-25 2006-02-07 Southern Methodist University System and method for controlling the size of the molten pool in laser-based additive manufacturing
US6940037B1 (en) 2003-08-25 2005-09-06 Southern Methodist University System and method for controlling welding parameters in welding-based deposition processes
EP2032345B1 (fr) 2006-06-20 2010-05-05 Katholieke Universiteit Leuven Procédure et appareil pour la surveillance in situ et la commande par rétroaction d'un traitement sélectif de poudre laser
US20080314878A1 (en) 2007-06-22 2008-12-25 General Electric Company Apparatus and method for controlling a machining system
CN102292187B (zh) 2008-11-21 2015-12-09 普雷茨特两合公司 用于监控要在工件上实施的激光加工过程的方法和装置以及具有这种装置的激光加工头
JP5172041B2 (ja) 2009-07-20 2013-03-27 プレシテック カーゲー レーザ加工ヘッドおよびレーザ加工ヘッドの焦点位置の変化を補償するための方法
EP2585975B1 (fr) 2010-06-28 2018-03-21 Precitec GmbH & Co. KG Procédé permettant de classer une multitude d'images enregistrées par une caméra observant une zone de traitement et tête de traitement de matériaux au laser utilisant ledit procédé
DE202010010771U1 (de) 2010-07-28 2011-11-14 Cl Schutzrechtsverwaltungs Gmbh Laserschmelzvorrichtung zum Herstellen eines dreidimensionalen Bauteils
US10124410B2 (en) 2010-09-25 2018-11-13 Ipg Photonics Corporation Methods and systems for coherent imaging and feedback control for modification of materials
US9710730B2 (en) * 2011-02-11 2017-07-18 Microsoft Technology Licensing, Llc Image registration
WO2013019663A2 (fr) 2011-07-29 2013-02-07 Carnegie Mellon University Cartographie de processus de géométrie de cuve d'immersion
EP2769799B1 (fr) 2011-10-17 2019-04-03 Kabushiki Kaisha Toshiba Dispositif d'irradiation laser et procédé de diagnostic d'intégrité de tête d'irradiation laser
US9117281B2 (en) * 2011-11-02 2015-08-25 Microsoft Corporation Surface segmentation from RGB and depth images
WO2013129270A1 (fr) * 2012-02-29 2013-09-06 株式会社村田製作所 Dispositif de protection contre les décharges électrostatiques et son procédé de fabrication
CN103294987A (zh) * 2012-03-05 2013-09-11 天津华威智信科技发展有限公司 指纹匹配方法与实现方式
US9939394B2 (en) 2012-08-17 2018-04-10 Carnegie Mellon University Process mapping of cooling rates and thermal gradients
WO2014039825A2 (fr) 2012-09-07 2014-03-13 Makerbot Industries, Llc Commutation de couleur pour une impression tridimensionnelle
JP6342912B2 (ja) * 2012-11-08 2018-06-13 ディーディーエム システムズ， インコーポレイテッド 金属構成要素の加法的製造および修復
US20170000784A1 (en) 2013-12-08 2017-01-05 Van Andel Research Institute Autophagy Inhibitors
DE102014202020B4 (de) 2014-02-05 2016-06-09 MTU Aero Engines AG Verfahren und Vorrichtung zur Bestimmung von Eigenspannungen eines Bauteils
GB201402804D0 (en) * 2014-02-17 2014-04-02 Univ Manchester Implants
JP6193493B2 (ja) 2014-06-20 2017-09-06 株式会社フジミインコーポレーテッド 粉末積層造形に用いる粉末材料およびそれを用いた粉末積層造形法
US20160016259A1 (en) 2014-07-21 2016-01-21 Siemens Energy, Inc. Optimization of melt pool shape in a joining process
US9999924B2 (en) 2014-08-22 2018-06-19 Sigma Labs, Inc. Method and system for monitoring additive manufacturing processes
US9981341B2 (en) 2014-08-25 2018-05-29 Jyoti Mazumder Smart additive manufacturing system (SAMS)
US9821410B2 (en) 2014-09-16 2017-11-21 Honeywell International Inc. Turbocharger shaft and wheel assembly
US20160098825A1 (en) 2014-10-05 2016-04-07 Sigma Labs, Inc. Feature extraction method and system for additive manufacturing
US10810731B2 (en) * 2014-11-07 2020-10-20 Arizona Board Of Regents On Behalf Of Arizona State University Information coding in dendritic structures and tags
US10048661B2 (en) 2014-12-17 2018-08-14 General Electric Company Visualization of additive manufacturing process data
US10353376B2 (en) * 2015-01-29 2019-07-16 Arconic Inc. Systems and methods for modelling additively manufactured bodies
GB201510220D0 (en) 2015-06-11 2015-07-29 Renishaw Plc Additive manufacturing apparatus and method
JP6241458B2 (ja) 2015-07-14 2017-12-06 トヨタ自動車株式会社 肉盛層の品質判定方法及びレーザ肉盛装置
US20170071744A1 (en) * 2015-09-15 2017-03-16 Sulzhan Bali Composition of orthopedic knee implant and the method for manufacture thereof
US20170087634A1 (en) * 2015-09-30 2017-03-30 General Electric Company System and method for additive manufacturing process control
US10500675B2 (en) 2015-11-02 2019-12-10 General Electric Company Additive manufacturing systems including an imaging device and methods of operating such systems
KR20180082492A (ko) * 2015-11-16 2018-07-18 머티어리얼리스 엔브이 적층 가공 프로세스에서의 에러 검출
US11179807B2 (en) 2015-11-23 2021-11-23 Nlight, Inc. Fine-scale temporal control for laser material processing
JP6764228B2 (ja) * 2015-12-22 2020-09-30 株式会社フジミインコーポレーテッド 粉末積層造形に用いるための造形用材料
US10583532B2 (en) * 2015-12-28 2020-03-10 General Electric Company Metal additive manufacturing using gas mixture including oxygen
US20170239719A1 (en) 2016-02-18 2017-08-24 Velo3D, Inc. Accurate three-dimensional printing
US10831180B2 (en) * 2016-02-25 2020-11-10 General Electric Company Multivariate statistical process control of laser powder bed additive manufacturing
US10882140B2 (en) 2016-03-25 2021-01-05 Technology Research Association For Future Additive Manufacturing Three-dimensional laminating and shaping apparatus, control method of three-dimensional laminating and shaping apparatus, and control program of three-dimensional laminating and shaping apparatus
CN105811794B (zh) 2016-05-06 2018-03-30 上海海事大学 多电平逆变器的参考电压信号重构的容错控制方法
US11204597B2 (en) 2016-05-20 2021-12-21 Moog Inc. Outer space digital logistics system
US10372110B2 (en) 2016-06-17 2019-08-06 Hamilton Sundstrand Corporation Controlled thin wall thickness of heat exchangers through modeling of additive manufacturing process
DE102016212063A1 (de) 2016-07-01 2018-01-04 Eos Gmbh Electro Optical Systems Vorrichtung und Verfahren zur Bestrahlungssteuerung in einer Vorrichtung zum Herstellen eines dreidimensionalen Objekts
CN106363275B (zh) * 2016-10-25 2018-11-20 西南交通大学 基于电弧电压反馈的gtaw增材制造过程稳定性检测方法
US10919285B2 (en) 2016-11-07 2021-02-16 General Electric Company Method and system for x-ray backscatter inspection of additive manufactured parts
US11318535B2 (en) 2016-12-23 2022-05-03 General Electric Company Method for process control in additive manufacturing
US10821512B2 (en) 2017-01-06 2020-11-03 General Electric Company Systems and methods for controlling microstructure of additively manufactured components
US10234848B2 (en) 2017-05-24 2019-03-19 Relativity Space, Inc. Real-time adaptive control of additive manufacturing processes using machine learning
US10747202B2 (en) 2017-06-30 2020-08-18 General Electric Company Systems and method for advanced additive manufacturing
US9977425B1 (en) 2017-07-14 2018-05-22 General Electric Company Systems and methods for receiving sensor data for an operating manufacturing machine and producing an alert during manufacture of a part
CN107655831B (zh) * 2017-09-18 2018-09-25 华中科技大学 一种基于多波段耦合的增材制造过程熔池监测装置及方法
GB201718597D0 (en) * 2017-11-10 2017-12-27 Renishaw Plc Spatial mapping of sensor data collected during additive manufacturing
CN108608118A (zh) * 2018-05-03 2018-10-02 哈尔滨工业大学（威海） 基于熔池温度和尺寸测量的激光增材制造缺陷诊断方法
CN108788153A (zh) * 2018-08-27 2018-11-13 西安空天能源动力智能制造研究院有限公司 一种激光选区熔化加工过程实时质量监控装置及方法
US20200147868A1 (en) * 2018-11-09 2020-05-14 General Electric Company Method for Detecting Errors and Compensating for Thermal Dissipation in an Additive Manufacturing Process
US10828836B2 (en) * 2018-12-13 2020-11-10 General Electric Company Method for melt pool monitoring
US10894364B2 (en) * 2018-12-13 2021-01-19 General Electric Company Method for melt pool monitoring using geometric length
US11285671B2 (en) * 2018-12-13 2022-03-29 General Electric Company Method for melt pool monitoring using Green's theorem
US10828837B2 (en) * 2018-12-13 2020-11-10 General Electric Company Method for melt pool monitoring using algebraic connectivity
CN110788444A (zh) * 2019-11-28 2020-02-14 上海工程技术大学 一种电弧增材制造熔池动态检测装置及方法

Also Published As

Publication number Publication date
CN111318697A (zh) 2020-06-23
US20200189195A1 (en) 2020-06-18
US11020907B2 (en) 2021-06-01
CN111318697B (zh) 2023-01-03
EP3666424A1 (fr) 2020-06-17

Similar Documents

Publication Publication Date Title
US11679548B2 (en) Method for melt pool monitoring
CN108290219B (zh) 增材制造方法及设备
CN107037122B (zh) 用于加性制造过程的非接触式声学检查方法
CN110114203B (zh) 用于增材制造中的处理控制的方法
CA2948261C (fr) Surveillance d'ecoulement de gaz dans la fabrication additive
EP3667565A1 (fr) Procédé de surveillance de bassin de fusion utilisant l'apprentissage machine
EP3666427B1 (fr) Procédé de surveillance de bassin de fusion au moyen de la longueur géométrique
CN111168062B (zh) 用于检测增材制造处理中的错误的熔池监测系统和方法
EP3210713A1 (fr) Surveillance de puissance laser dans une fabrication additive
US20230141266A1 (en) Systems and Methods
EP3666426A1 (fr) Procédé de surveillance de bassin de fusion utilisant une connectivité algébrique
US11285671B2 (en) Method for melt pool monitoring using Green's theorem
EP3666424B1 (fr) Procédé de surveillance de bassin de fusion utilisant des dimensions fractales

Legal Events

Date Code Title Description
PUAI Public reference made under article 153(3) epc to a published international application that has entered the european phase

Free format text: ORIGINAL CODE: 0009012

STAA Information on the status of an ep patent application or granted ep patent

Free format text: STATUS: THE APPLICATION HAS BEEN PUBLISHED

AK Designated contracting states

Kind code of ref document: A1

Designated state(s): AL AT BE BG CH CY CZ DE DK EE ES FI FR GB GR HR HU IE IS IT LI LT LU LV MC MK MT NL NO PL PT RO RS SE SI SK SM TR

AX Request for extension of the european patent

Extension state: BA ME

STAA Information on the status of an ep patent application or granted ep patent

Free format text: STATUS: REQUEST FOR EXAMINATION WAS MADE

17P Request for examination filed

Effective date: 20201214

RBV Designated contracting states (corrected)

Designated state(s): AL AT BE BG CH CY CZ DE DK EE ES FI FR GB GR HR HU IE IS IT LI LT LU LV MC MK MT NL NO PL PT RO RS SE SI SK SM TR

RIN1 Information on inventor provided before grant (corrected)

Inventor name: SPEARS, THOMAS GRAHAM

REG Reference to a national code

Ref country code: DE

Ref legal event code: R079

Ref document number: 602019025092

Country of ref document: DE

Free format text: PREVIOUS MAIN CLASS: B22F0003105000

Ipc: B22F0010850000

GRAP Despatch of communication of intention to grant a patent

Free format text: ORIGINAL CODE: EPIDOSNIGR1

STAA Information on the status of an ep patent application or granted ep patent

Free format text: STATUS: GRANT OF PATENT IS INTENDED

RIC1 Information provided on ipc code assigned before grant

Ipc: B22F 12/44 20210101ALN20220902BHEP

Ipc: B22F 10/73 20210101ALN20220902BHEP

Ipc: B22F 10/25 20210101ALN20220902BHEP

Ipc: B22F 10/28 20210101ALN20220902BHEP

Ipc: B29C 64/153 20170101ALI20220902BHEP

Ipc: B22F 10/36 20210101ALI20220902BHEP

Ipc: B22F 12/90 20210101ALI20220902BHEP

Ipc: B29C 64/393 20170101ALI20220902BHEP

Ipc: B33Y 10/00 20150101ALI20220902BHEP

Ipc: B33Y 50/00 20150101ALI20220902BHEP

Ipc: B33Y 50/02 20150101ALI20220902BHEP

Ipc: B29C 64/386 20170101ALI20220902BHEP

Ipc: B22F 10/85 20210101AFI20220902BHEP

RIC1 Information provided on ipc code assigned before grant

Ipc: B22F 12/44 20210101ALN20220909BHEP

Ipc: B22F 10/73 20210101ALN20220909BHEP

Ipc: B22F 10/25 20210101ALN20220909BHEP

Ipc: B22F 10/28 20210101ALN20220909BHEP

Ipc: B29C 64/153 20170101ALI20220909BHEP

Ipc: B22F 10/36 20210101ALI20220909BHEP

Ipc: B22F 12/90 20210101ALI20220909BHEP

Ipc: B29C 64/393 20170101ALI20220909BHEP

Ipc: B33Y 10/00 20150101ALI20220909BHEP

Ipc: B33Y 50/00 20150101ALI20220909BHEP

Ipc: B33Y 50/02 20150101ALI20220909BHEP

Ipc: B29C 64/386 20170101ALI20220909BHEP

Ipc: B22F 10/85 20210101AFI20220909BHEP

INTG Intention to grant announced

Effective date: 20221011

GRAS Grant fee paid

Free format text: ORIGINAL CODE: EPIDOSNIGR3

GRAA (expected) grant

Free format text: ORIGINAL CODE: 0009210

STAA Information on the status of an ep patent application or granted ep patent

Free format text: STATUS: THE PATENT HAS BEEN GRANTED

AK Designated contracting states

Kind code of ref document: B1

Designated state(s): AL AT BE BG CH CY CZ DE DK EE ES FI FR GB GR HR HU IE IS IT LI LT LU LV MC MK MT NL NO PL PT RO RS SE SI SK SM TR

REG Reference to a national code

Ref country code: GB

Ref legal event code: FG4D

REG Reference to a national code

Ref country code: CH

Ref legal event code: EP

Ref country code: AT

Ref legal event code: REF

Ref document number: 1547326

Country of ref document: AT

Kind code of ref document: T

Effective date: 20230215

REG Reference to a national code

Ref country code: IE

Ref legal event code: FG4D

REG Reference to a national code

Ref country code: DE

Ref legal event code: R096

Ref document number: 602019025092

Country of ref document: DE

REG Reference to a national code

Ref country code: LT

Ref legal event code: MG9D

REG Reference to a national code

Ref country code: NL

Ref legal event code: MP

Effective date: 20230208

P01 Opt-out of the competence of the unified patent court (upc) registered

Effective date: 20230516

REG Reference to a national code

Ref country code: AT

Ref legal event code: MK05

Ref document number: 1547326

Country of ref document: AT

Kind code of ref document: T

Effective date: 20230208

PG25 Lapsed in a contracting state [announced via postgrant information from national office to epo]

Ref country code: RS

Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT

Effective date: 20230208

Ref country code: PT

Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT

Effective date: 20230609

Ref country code: NO

Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT

Effective date: 20230508

Ref country code: NL

Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT

Effective date: 20230208

Ref country code: LV

Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT

Effective date: 20230208

Ref country code: LT

Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT

Effective date: 20230208

Ref country code: HR

Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT

Effective date: 20230208

Ref country code: ES

Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT

Effective date: 20230208

Ref country code: AT

Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT

Effective date: 20230208

PG25 Lapsed in a contracting state [announced via postgrant information from national office to epo]

Ref country code: SE

Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT

Effective date: 20230208

Ref country code: PL

Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT

Effective date: 20230208

Ref country code: IS

Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT

Effective date: 20230608

Ref country code: GR

Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT

Effective date: 20230509

Ref country code: FI

Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT

Effective date: 20230208

PG25 Lapsed in a contracting state [announced via postgrant information from national office to epo]

Ref country code: SM

Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT

Effective date: 20230208

Ref country code: RO

Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT

Effective date: 20230208

Ref country code: EE

Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT

Effective date: 20230208

Ref country code: DK

Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT

Effective date: 20230208

Ref country code: CZ

Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT

Effective date: 20230208

REG Reference to a national code

Ref country code: DE

Ref legal event code: R097

Ref document number: 602019025092

Country of ref document: DE

PG25 Lapsed in a contracting state [announced via postgrant information from national office to epo]

Ref country code: SK

Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT

Effective date: 20230208

PLBE No opposition filed within time limit

Free format text: ORIGINAL CODE: 0009261

STAA Information on the status of an ep patent application or granted ep patent

Free format text: STATUS: NO OPPOSITION FILED WITHIN TIME LIMIT

26N No opposition filed

Effective date: 20231109

PGFP Annual fee paid to national office [announced via postgrant information from national office to epo]

Ref country code: GB

Payment date: 20231019

Year of fee payment: 5

PG25 Lapsed in a contracting state [announced via postgrant information from national office to epo]

Ref country code: SI

Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT

Effective date: 20230208

PGFP Annual fee paid to national office [announced via postgrant information from national office to epo]

Ref country code: FR

Payment date: 20231020

Year of fee payment: 5

Ref country code: DE

Payment date: 20231019

Year of fee payment: 5

PG25 Lapsed in a contracting state [announced via postgrant information from national office to epo]

Ref country code: IT

Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT

Effective date: 20230208

REG Reference to a national code

Ref country code: CH

Ref legal event code: PL

PG25 Lapsed in a contracting state [announced via postgrant information from national office to epo]

Ref country code: MC

Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT

Effective date: 20230208

PG25 Lapsed in a contracting state [announced via postgrant information from national office to epo]

Ref country code: LU

Free format text: LAPSE BECAUSE OF NON-PAYMENT OF DUE FEES

Effective date: 20231120

PG25 Lapsed in a contracting state [announced via postgrant information from national office to epo]

Ref country code: CH

Free format text: LAPSE BECAUSE OF NON-PAYMENT OF DUE FEES

Effective date: 20231130

PG25 Lapsed in a contracting state [announced via postgrant information from national office to epo]

Ref country code: MC

Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT

Effective date: 20230208

Ref country code: LU

Free format text: LAPSE BECAUSE OF NON-PAYMENT OF DUE FEES

Effective date: 20231120

Ref country code: CH

Free format text: LAPSE BECAUSE OF NON-PAYMENT OF DUE FEES

Effective date: 20231130

REG Reference to a national code

Ref country code: BE

Ref legal event code: MM

Effective date: 20231130

REG Reference to a national code

Ref country code: IE

Ref legal event code: MM4A

PG25 Lapsed in a contracting state [announced via postgrant information from national office to epo]

Ref country code: IE

Free format text: LAPSE BECAUSE OF NON-PAYMENT OF DUE FEES

Effective date: 20231120

PG25 Lapsed in a contracting state [announced via postgrant information from national office to epo]

Ref country code: BE

Free format text: LAPSE BECAUSE OF NON-PAYMENT OF DUE FEES

Effective date: 20231130